ToC

  • Obesity & Adipose Tisssue
  • Personalized Medicine (PM) & Omics
  • The FATe project
    • Biomarkers
    • Targetable genes
    • Gene Therapy

Obesity

An evolutionary mismatch…

Modified from Shanmugasundaram et al, Curr Oral Health Rep (2024)

Death statistic according to cause of death.
Provisional data (June 2024). INE

Modified from Nuttall et al., Nutr Today 2015

Obesity definition

Obesity Medicine Association has defined obesity as:

“A chronic, progressive, relapsing, and treatable multi-factorial, neurobehavioral disease,

wherein an increase in body fat promotes adipose tissue dysfunction and abnormal fat mass physical forces,

resulting in adverse metabolic, biomechanical, and psychosocial health consequences.

Obesity and White adipose tissue (WAT)

  • Main site for safe energy storage

Obesity and White adipose tissue (WAT)

  • Endocrine organ that secretes cytokines and adipokines

Obesity and White adipose tissue (WAT)

  • Highly heterogeneous

Obesity and White adipose tissue (WAT)

Personalized Medicine

Personalised Medicine (PM) refers to a medical model using characterisation of individuals’ phenotypes and genotypes (e.g. molecular profiling, medical imaging, lifestyle data) for tailoring the right therapeutic strategy for the right person at the right time, and/or to determine the predisposition to disease and/or to deliver timely and targeted prevention

Key Aspect: PM aims for optimal outcomes by helping clinicians select the treatments best suited to individual patients.

Biology is complex…

  • 3 Billion Base Pairs, forming the blueprint of life with extensive information encoded within. Each Cell with Its Own Epigenetic Program

  • 37 Trillion Cells, each functioning and interacting in a complex, dynamic environment

  • 200 Different Cell Types, each specialized for unique roles, from neurons that transmit signals to adipocytes that store fat

  • Huge Complexity Within Each Cell, numerous organelles and molecular machines working in concert, with an unique Set of Expressed Genes and Proteins

Computational Biology in PM

Definition of Computational Biology: Application of data-analytical methods, mathematical modeling, and computational simulation to study biological systems.

Role in PM: Facilitates analysis of complex data (genomics, proteomics) to understand disease mechanisms.

Computational Biology is still Biology

Omic Techniques: Definion

Relates to a branch of biological science specifically focusing on the comprehensive study of sets of biological entities.

“Omic” technologies examine the roles, relationships, and actions of various types of biological molecules that make up the cells and tissues of an organism.

Omic Techniques:

  • Genomics: Uses sequencing and exome sequencing to study genes and genome structure.
  • Epigenomics: Study changes to the DNA that do not alter the DNA sequence itself but affect gene expression and function.
  • Transcriptomics: Focuses on the analysis of the transcriptome, the complete set of RNA transcripts produced by the genome at any one time.
  • Proteomics: Employs mass spectrometry and ELISA to analyze proteins and peptides.
  • Metabolomics: Analyzes metabolites using mass spectrometry and NMR spectroscopy.

Need for Personalized Medicine in Obesity

  • Complexity of Obesity: Influenced by genetics, time, environment, and lifestyle, making it complex to treat.

  • Personalization in Obesity: Personalized approaches address specific metabolic profiles, genetic predispositions, enviromental cues, and responses to diet and exercise.

  • Benefits: Improved prediction, prevention, and treatment of obesity-related complications.

Are We There Yet?…

Progress Towards True Personalized Medicine in Obesity

  • Current Status: True personalized medicine in obesity is not yet fully achievable.
  • Stratification Using Omics to develop biomarkers which help stratify the population into different risk subgroups.

FATe project (2013- )

Adipose tissue expandability

Adipose tissue expandability

1. Stratification of obese individuals

Metabolic characterization of the different subtypes of obesity

SC / Vis ratio

SC / vis ratio = Subcutaneous adipose area / Visceral adipose area

Identification of differentially expressed genes in scWAT according to the SC/Vis ratio

Validation of AT expression and serum levels of CCDC3 and ISM1

Biomarker evaluation: ROC curve

ISM1 is a biomarker of fat partitioning

ISM1 predicts abdominal fat partitioning and act as biomarker for evaluating obesity-related health risk

2. Identification of targetable genes in scWAT involved in the development and progression of non-alcoholic fatty liver disease (NAFLD)

Identification of genes involved in AT– liver crosstalk

Validation of candidate genes in a second cohort with liver histology

Expression of selected genes in adipocytes of patients with different degrees of liver steatosis

Expression of selected genes in adipocytes of patients with different degrees of liver steatosis

Targetable genes in scWAT

SOCS3, SIK1, GADD45B, and DUSP1 showed a differential expression pattern in both scWAT and hMSC-derived adipocytes, where their expression paralleled steatosis degree

3.Gene therapy in obesity

Modulation (knock-down) of target genes

Reduced expression of target genes using CRISPR

Gene editing in adipocytes reduced lipid deposition in hepatocytes

Summary (… so far)

  • It is critical to distinguish adipose tissue location to classify obesity phenotypes. The Subcutaneous/Visceral ratio is an accurate metric to classify the metabolic status of individuals with similar perceived obesity (same BMI and same waist circumference).

  • ISM1 expression levels in scWAT and its serum levels exhibited a correlation with the SFA/VFA ratio. These findings suggest that ISM1 could predict abdominal fat partitioning and act as a potential biomarker for evaluating obesity-related health risks.

  • SOCS3, DUSP1, SIK1 and GADD45B showed a differential expression pattern in both scWAT and hADMSC-derived adipocytes of patients with NAFLD. Their expression paralleled steatosis degree.

  • Editing out SOCS3, DUSP1, and SIK1 using CRISP/Cas9 technology reduced their expression in hADMSC without conditioning its adipogenic capacity, highlighting the potential of this gene editing tool to treat metabolic complications.